Journal of the Korean Society of Clothing and Textiles (한국의류학회지)

The Korean Society of Clothing and Textiles (한국의류학회)
권호 표지
DOI QR코드

DOI QR Code

Classification System of Fashion Emotion for the Standardization of Data

데이터 표준화를 위한 패션 감성 분류 체계

  • Park, Nanghee (Dept. of Clothing & Textiles, Chungnam National University) ;
  • Choi, Yoonmi (Dept. of Clothing & Textiles, Chungnam National University)
  • Received : 2021.06.29
  • Accepted : 2021.11.12
  • Published : 2021.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

Keywords

Acknowledgement

본 논문은 2020년도 정부(교육부)의 재원으로 한국연구재단 기초연구사업의 지원을 받아 수행된 연구임(No.2020R1A6A301095745).

References

  1. Ahn, C. M. (2019). Hierarchical category classification of fashion item images (Unpublished master's thesis). Seoul National University, Seoul.
  2. An, H. (2017). A study on the sentiment analysis in fashion design using big data - Focused on text mining and semantic network analysis - (Unpublished doctoral dissertation). Ewha Womans University, Seoul.
  3. An, H., & Lee, I. (2013). Extraction of fashion sensibility vocabulary for globalization. Bulletin of Korean Society of Basic Design & Art, 14(3), 133-141.
  4. Bae, H. J., & Chung, I. H. (2006). The desired self-images and the fashion product unities of male college students according to situation. Journal of the Korean Society of Clothing and Textiles, 30(7), 1135-1145.
  5. Baek, H.-E., & Kim, Y.-S. (2011). Characteristics of total coord ination in the pursuit of fashion sensibility among women in their 20's. The Research Journal of the Costume Culture, 19(6), 1163-1176. doi:10.29049/rjcc.2011.19.6.1163
  6. Conner, B. H., Peters, K., & Nagasawa, R. H. (1975). Person and costume: Effects on the formation of first impressions. Home Economics Research Journal, 4(1), 32-41. doi:10.1177/1077727X7500400103
  7. Chung, E.-S. (2000). Clothes selection in accordance with job characteristic and working place situation of a professional women in industry (Unpublished doctoral dissertation). Sookmyung Women's University, Seoul.
  8. Chung, I.-H. (2001). The study on desired image and fabric preference of woman college student for apparel. The Research Journal of the Costume Culture, 9(4), 629-638.
  9. Chung, I.-H., & Rhee, E.-Y. (1992). A study on clothing images: Their constructing factors and evaluative dimensions. Journal of the Korean Society of Clothing and Textiles, 16(4), 379-391.
  10. Damhorst, M. L. (1985). Meanings of clothing cues in social context. Clothing and Textiles Research Journal, 3(2), 39-48. doi:10.1177/0887302X8500300207
  11. Davis, L. L. (1985). Sex, gender identity, and behavior concerning sex-related clothing. Clothing and Textiles Research Journal, 3(2), 20-24. doi:10.1177/0887302X8500300203
  12. Forsythe, S. M. (1988). Effect of clothing masculinity on perceptions of managerial traits: Does gender of the perceiver make a difference? Clothing and Textiles Research Journal, 6(2), 10-16. doi:10.1177/0887302X8800600202
  13. Han, J. S. (2020, August 5). 세계는 '데이터 산업' 전쟁 중 [The world is at war with the 'data industry']. Futurekorea Weekly. Retrieved from http://www.futurekorea.co.kr/news/articleView.html?idxno=137730
  14. Hong, H. R., & Kim, Y. I. (2016). The preferred fashion style and self-image that Korean career women's seek according to daily situations. Journal of the Korean Society of Costume, 66(7), 50-68. doi:10.7233/jksc.2016.66.7.050
  15. Jang, D., & Chun, J. (2007). Automated classification scheme generation using product attribute information. The KIPS Transactions: Part D, 14-D(5), 491-500. doi:10.3745/KIPSTD.2007.14-D.5.491
  16. Jeong, S., Vicent, M., Kim, J. K., Lee, B. W., Lee, S. Y., Lee, M. J., & Lee, W. J. (2017). The application of deep learning for image attribute recognition and classification. Proceedings of the Korea Software Congress 2017, Korea, 877-879.
  17. Jin, H., Piao, Z., Gu, Y. H., & Yoo, S. J. (2020). A survey of fashion datasets for AI training. Proceedings of 2020 The Korean Institute of Broadcast and Media Engineers Summer Conference, Korea, 637-642.
  18. Kim, I.-B., & Yoo, T.-S. (1999). A study of relations between clothes image types and design factors. Journal of the Korean Society of Costume, 45, 103-119.
  19. Kim, J.-Y., & Lee, K.-H. (2009). Analysis of fashion sensibility on the compound fashion image of contemporary fashion. Journal of the Korean Society for Clothing Industry, 11(1), 6-13.
  20. Kim, K.-H., Park, Y.-S., & Jung, E.-C. (2011). Development of classification system model of design information for integrated design research. Journal of Korean Society of Design Science, 24(3), 55-66.
  21. Kim, Y. J. (2002). A study of clothing formative properties in fashion sensibility and emotion (Unpublished doctoral dissertation). Pusan National University, Busan.
  22. Kim, Y.-J., & Lee, K.-H. (2004). Formative properties of sensibility and emotion in fashion. Journal of the Korean Society of Clothing and Textiles, 28(1), 34-44.
  23. Kim, Y. K. (2017). Study on classification of associated words of fashion image words through analogical transfer-Focused on the image words of feminine, mannish, classic and avant-garde-. Journal of the Korean Society of Costume, 67(5), 1-16. doi:10.7233/jksc.2017.67.5.001
  24. Kim, Y. K. (2020). A study on the dimension of design idea through the analysis of words that remind of fashion image words-Focusing on classic and avant-garde imaged language-. Journal of the Korean Society of Clothing and Textiles, 44(3), 413-426. doi:10.5850/JKSCT.2020.44.3.413
  25. Kim, Y. S. (2018, March 1). "'데이터'는 4차 산업혁명 시대의 '원유'이다" ["'Data' is 'crude oil' in the era of the 4th industrial revolution"]. ComputerWorld. Retrieved from https://www.comworld.co.kr/news/articleView.html?idxno=49399
  26. Kwon, S. (2019). A study on the fashion sensibility of athleisure look in image-based SNS (Unpublished doctoral dissertation). Ewha Womans University, Seoul.
  27. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444. doi:10.1038/nature14539
  28. Lee, E. R., & Lee, K. H. (1996). A study on the visual evaluation about silhouette image-Based on X-line-. Journal of the Korean Society of Clothing and Textiles, 20(4), 631-646.
  29. Lee, E.-R., & Lee, K.-H. (2007). A study on fashion sensibility of adult women's town wear. Journal of the Korean Society for Clothing Industry, 9(4), 380-390.
  30. Lee, K. H. (2001). A study on the development of fashion sensibility. Journal of the Korean Society of Clothing and Textiles, 25(3), 537-547.
  31. Lee, K.-H., & Kim, Y.-J. (2001a). A study of the relationship between fashion sensibility and formative properties in clothing. Journal of the Korean Society of Clothing and Textiles, 25(5), 845-855.
  32. Lee, K. H., & Kim, Y. J. (2001b). Process of the scale in fashion sensibility. Science of Emotion & Sensibility, 4(1), 33-42.
  33. Lee, K.-H., & Kim, Y.-J. (2003). A study on the development of fashion sensibility (Part II). Journal of the Korean Society of Clothing and Textiles, 27(5), 505-516.
  34. Lee, M.-H. (2002). The effect of contexts, clothing type, and clothing color on women's impression formation. Journal of the Korean Society of Clothing and Textiles, 26(3/4), 503-514.
  35. Lee, S.-C., Jeong, H.-D., Park, S.-T., & Kim, S.-H. (2017). Deep learning. Journal of KSNVE, 27(3), 19-25.
  36. Lee. Y.-J. (2001). Development of color and textile database system for fashion design based on classification of the color and textile images. Journal of Korean Traditional Costume, 4(1), 123-136.
  37. Liu, Z., Luo, P., Qiu, S., Wang, X., & Tang, X. (2016). Deep-Fashion: Powering robust clothes recognition and retrieval with rich annotations. Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), USA, 1096-1104. doi:10.1109/CVPR.2016.124
  38. Oh, M.-J. (2015). A study of the fashion design concepts based on the difference in fashion-related emotion and sensibility between fashion experts and non-experts (Unpublished master's thesis). Yonsei University, Seoul.
  39. OMNIOUS. (2019, October 1). 상품 속성 입력 자동화로 우리 쇼핑몰이 달라졌어요! [Our shopping mall has changed by automating product attribute input!]. 옴니어스 인사이트 [OMNIOUS Insight]. Retrieved from https://brunch.co.kr/@omniousofficial/67
  40. Pack, E., & Chung, M.-S. (1997). Situational impression on body exposing clothing. Journal of Human Ecology, 7, 23-34.
  41. Paek, S. L. (1986). Effect of garment style of the perception of personal traits. Clothing and Textiles Research Journal, 5(1), 10-16. doi:10.1177/0887302X8600500102
  42. Park, E. J., & Rhee, E. Y. (1993). A theoretical study on situational influences in clothing purchase behavior. Journal of the Korean Society of Clothing and Textiles, 17(2), 219-231.
  43. Park, E. J., & Rhee, E. Y. (1995). A typology of apparel usage situations among female consumers. Journal of the Korean Society of Clothing and Textiles, 19(5), 713-722.
  44. Park, N., & Choi, Y. (2020a). A form attribute classification system for fashion items. International Journal of Fashion Design, Technology and Education, 13(1), 11-19. doi:10.1080/17543266.2019.1664641
  45. Park, N., & Choi, Y. (2020b). Color & texture attribute classification system of fashion item image for standardizing learning data in fashion AI. Journal of the Korean Society of Clothing and Textiles, 44(2), 354-368. doi:10.5850/JKSCT.2020.44.2.354
  46. Rowold, K. L. (1984). Sensitivity to the appearance of others and projection as factors in impression formation. Home Economics Research Journal, 13(2), 105-111. doi:10.1177/1077727X8401300202
  47. Song, H. J., Kim, H. W., Chung, E., Oh, S., Lee, J. W., Kang, D., ... Lee, Y. K. (2019). Self-improving artificial intelligence technology. Electronics and Telecommunications Trends, 34(4), 43-54. doi:10.22648/ETRI.2019.J.340405
  48. Sung, J.-K., Park, S.-M., Sin, S.-Y., Kim, Y.-B., & Kim, Y.-G. (2017). Deep learning-based product image classification system and its usability evaluation for the O2O shopping mall platform. The Journal of The Institute of Internet, Broadcasting and Communication, 17(3), 227-234. doi:10.7236/JIIBC.2017.17.3.227
  49. Sweat, S. J., & Zentner, M. A. (1985). Female appearance presentation: Gender differences in social attribution and situational choice. Home Economics Research Journal, 14(2), 175-186. doi:10.1177/1077727X8501400201
  50. The Korean Language Society. (1991). 우리말 큰사전 [Grand dictionary of Korean]. Seoul: Omungak.
  51. Wong, C. W. K. (2018, May). Challenges & opportunities of AI in fashion & textile industry (AI and computer vision). Paper presented at 2018 International Conference on Clothing & Textiles (ICCT), Seoul
  52. Zou, X., Kong, X., Wong, W., Wang, C., Liu, Y., & Cao, Y. (2019). FashionAI: A hierarchical dataset for fashion understanding. Proceedings of 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), USA, 296-304. doi:10.1109/CVPRW.2019.00039